Understanding Variance Analysis

Chapter 20: Planning for Implementation - Page 20.9

Understanding Variance Analysis

Many businesses, especially the small, entrepreneurial kind, ignore or forget the other half of the budgeting. Budgets are too often proposed, discussed, accepted, and forgotten. Variance analysis looks after-the-fact at what caused a difference between plan vs. actual. Good management looks at what that difference means to the business.

Variance analysis ranges from simple and straightforward to sophisticated and complex. Some cost-accounting systems separate variances into many types and categories. Sometimes a single result can be broken down into many different variances, both positive and negative.

The most sophisticated systems separate unit and price factors on materials, hours worked, cost-per-hour on direct labor, and fixed and variable overhead variances. Though difficult, this kind of analysis can be invaluable in a complex business.

Look for Specifics

This presentation of variances shows how important good analysis is. In theory, the positive variances are good news because they mean spending less than budgeted. The negative variance means spending more than the budget.

Variance Analysis for Sample Company

Continuing our example, the $5,000 positive variance in advertising in January means $5,000 less than planned was spent, and the $7,000 positive variance for literature in February means $7,000 less than planned was spent. The negative variance for advertising in February and March, and the negative variance for literature in March, show that more was spent than was planned for those items.

Evaluating these variances takes thought. Positive variances aren't always good news. For example:

The positive variance of $5,000 in advertising means that money wasn't spent, but it also means that advertising wasn't placed. Systems sales are way below expectations for this same period — could the advertising missed in January be a possible cause?
For literature, the positive $7,000 in February may be evidence of a missed deadline for literature that wasn't actually completed until March. If so, at least it appears that the costs on completion were $6,401, a bit less than the $7,000 planned.

Among the larger single variances for an expense item in a month shown in the illustration was the positive $7,000 variance for the new literature expenses in February. Is this good news or bad news? Every variance should stimulate questions.

Why did one project cost more or less than planned?
Were objectives met?
Is a positive variance a cost saving or a failure to implement?
Is a negative variance a change in plans, a management failure, or an unrealistic budget?

A variance table can provide management with significant information. Without this data, some of these important questions might go unasked.

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